def visualize_sampling3D(self, data_dict, only_pc=False):
import vtkplotter
from matplotlib import cm
cmap = cm.get_cmap('jet')
samples = data_dict[f'samples_geo']
labels = data_dict[f'labels_geo']
colors = cmap(labels / labels.max())[:, :3]
# [-1, 1]
points = samples
# create plot
vp = vtkplotter.Plotter(title="", size=(1500, 1500))
vis_list = []
if not only_pc:
# create a mesh
mesh = data_dict['mesh']
faces = mesh.faces
verts = mesh.verts
mesh = trimesh.Trimesh(verts, faces)
mesh.visual.face_colors = [200, 200, 250, 255]
vis_list.append(mesh)
# create a pointcloud
pc = vtkplotter.Points(points, r=12, c=np.float32(colors))
vis_list.append(pc)
vp.show(*vis_list, bg="white", axes=1, interactive=True)
def visualize_sampling3D(self, data_dict):
import vtkplotter
samples = data_dict[f'samples_geo']
labels = data_dict[f'labels_geo']
colors = np.stack([labels, labels, labels], axis=1)
mesh = data_dict['mesh']
faces = mesh.faces
# [-1, 1]
points = samples
verts = mesh.verts
# create plot
vp = vtkplotter.Plotter(title="", size=(1500, 1500))
vis_list = []
# create a mesh
mesh = trimesh.Trimesh(verts, faces)
mesh.visual.face_colors = [200, 200, 250, 255]
vis_list.append(mesh)
# create a pointcloud
pc = vtkplotter.Points(points, r=12, c=np.float32(colors))
vis_list.append(pc)
vp.show(*vis_list, bg="white", axes=1, interactive=True)
def plot_mask3D(mask=None,
title="",
point_coords=None,
figsize=1500,
point_marker_size=8,
interactive=True):
'''
Simple plotting tool to show intermediate mask predictions and points
where PointRend is applied.
Args:
mask (Tensor): mask prediction of shape DxHxW
title (str): title for the plot
point_coords ((Tensor, Tensor, Tensor)): x and y and z point coordinates
figsize (int): size of the figure to plot
point_marker_size (int): marker size for points
'''
import trimesh
import vtkplotter
from skimage import measure
vp = vtkplotter.Plotter(title=title, size=(figsize, figsize))
vis_list = []
if mask is not None:
mask = mask.detach().to("cpu").numpy()
mask = mask.transpose(2, 1, 0)
# marching cube to find surface
verts, faces, normals, values = measure.marching_cubes_lewiner(
mask, 0.5, gradient_direction='ascent')
# create a mesh
mesh = trimesh.Trimesh(verts, faces)
mesh.visual.face_colors = [200, 200, 250, 100]
vis_list.append(mesh)
if point_coords is not None:
point_coords = torch.stack(point_coords, 1).to("cpu").numpy()
# import numpy as np
# select_x = np.logical_and(point_coords[:, 0] >= 16, point_coords[:, 0] <= 112)
# select_y = np.logical_and(point_coords[:, 1] >= 48, point_coords[:, 1] <= 272)
# select_z = np.logical_and(point_coords[:, 2] >= 16, point_coords[:, 2] <= 112)
# select = np.logical_and(np.logical_and(select_x, select_y), select_z)
# point_coords = point_coords[select, :]
pc = vtkplotter.Points(point_coords, r=point_marker_size, c='red')
vis_list.append(pc)
vp.show(*vis_list,
bg="white",
axes=1,
interactive=interactive,
azimuth=30,
elevation=30)
def save_pts_to_vtk(pts, save_path="./test.vtk"):
"""
将牙龈点pts格式转为vtk格式
@pts: 点集 [[x, y, z], [x, y, z], ...]
@save_path: 保存路径
return: None
"""
import vtkplotter as vtkp
vtk_point = vtkp.Points(pts.reshape(-1, 3))
vtkp.write(vtk_point, save_path, binary=False)
def pts_to_vtk(self):
"""
将牙龈点pts格式转为vtk格式
@pts: 点集 [[x, y, z], [x, y, z], ...]
@save_path: 保存路径
return: None
"""
import vtkplotter as vtkp
save_path = os.path.join(self.show_path,
os.path.basename(self.obj_path)[:-4])
if not os.path.isdir(save_path):
os.makedirs(save_path)
save_path = os.path.join(save_path, "test.vtk")
vtk_point = vtkp.Points(self.gum_line_pts.reshape(-1, 3))
vtkp.write(vtk_point, save_path, binary=False)
a = vtk.load('tayl.stl')
sc = [c[1] for c in a.getPoints()]
a.pointColors(sc)
b = a.ybounds()
i = a.isolines(200, b[0], b[1])
i2 = a.isolines(50, b[1]*0.7, b[1]).clean()
ii = i.clean()
ii2 = i2.clean()
pnts1 = np.array([tuple(p) for p in ii.getPoints()], dtype=[
('x', float), ('y', float), ('z', float)])
pnts2 = np.array([tuple(p) for p in ii2.getPoints()], dtype=[
('x', float), ('y', float), ('z', float)])
g1 = group_by(pnts1, by='y', crit=1e-3)
g2 = group_by(pnts2, by='y', crit=1e-3)
p.show(a, i, i2, at=0, N=2)
p.show(vtk.Points(ii.getPoints()), vtk.Points(i2.getPoints()),
vtk.Points(g1[10].tolist(), c='green'),
vtk.Points(g1[0].tolist(), c='red'), at=1, interactive=True)
N = 10
z = []
r = []
for g in g1+g2:
if len(g) < 10:
continue
def residuals(p):
rez = []
for point in g:
rez.append((point['x']-p[0])**2+(point['z']-p[1])**2-p[2]**2)
return rez
"""
Script for visualizing subject's cortical surface and the implanted electrodes.
"""
import vtkplotter as vp
from util.surface import Surface
from util.contacts import Contacts
subject = "id001"
surf = Surface.from_npz_file(f"data/Geometry/{subject}/surface.npz")
contacts = Contacts(f"data/Geometry/{subject}/seeg.txt")
mesh = vp.Mesh([surf.vertices, surf.triangles], alpha=0.1)
points = vp.Points(contacts.xyz, r=20, c=(1, 1, 0))
vplotter = vp.Plotter(axes=0)
vplotter.show([mesh, points])